Update README

README.md

 # AutoKara
 
-Experiment in automatic karaoke timing.
-
-# Some documentation first
-
-Having a clean python environment:
-
-- https://realpython.com/python-virtual-environments-a-primer/
-
-An introduction to neural networks and deep learning:
-
-- http://neuralnetworksanddeeplearning.com
-
-
-## Extracting vocals from music
-
-- https://github.com/facebookresearch/demucs
-
-## Syllable segmentation
-
-### Symbolic methods
-
- - [Syllable segmentation](https://www.sciencedirect.com/science/article/pii/S1877050916319068/pdf?md5=abc426e84a71cd4f5c0e6bef9713643e&pid=1-s2.0-S1877050916319068-main.pdf&_valck=1)
- - [Syllable segmentation and recognition](https://cdn.intechopen.com/pdfs/15947/InTech-Syllable_based_speech_recognition.pdf)
- - [Onset detection with librosa](https://librosa.org/doc/latest/onset.html)
-
-### Machine Learning & Deep Learning methods
-
-[Using CNNs on spectrogram images](https://www.ofai.at/~jan.schlueter/pubs/2014_icassp.pdf) (Schlüter, Böck, 2014) :
- - [MADMOM implementation](https://madmom.readthedocs.io/en/v0.16/modules/features/onsets.html)
-
-[Aligning lyrics to song](https://github.com/jhuang448/LyricsAlignment-MTL) (Jiawen Huang, Emmanouil Benetos, Sebastian Ewert, 2022)
-
-### Other methods
-
-Other stuff goes here
-
-## Syllable recognition
-
-If we ever want to use an AI to identify syllables without a reference lyrics file 
-
+An experiment in automatic karaoke timing.
 
 # Installation
 
@@ -49,7 +10,7 @@ If we ever want to use an AI to identify syllables without a reference lyrics fi
 - FFmpeg
 - Python >= 3.8
 
-All other python modules can be installed directly through pip, see further.
+All other python modules can be installed directly through PIP, see next section.
 
 ## Install
 
@@ -86,7 +47,9 @@ Having a CUDA-capable GPU is optional, but can greatly reduce processing time in
 ## Configuration
 
 Autokara comes with a default config file in `autokara/default.conf`.
+
 If you want to tweak some values (enable CUDA, for example), you should add them to a new config file in your personal config directory : `~/.config/autokara/autokara.conf`.
+
 This new file has priority over the default one, which is used only as fallback for unspecified values.
 
 
@@ -158,4 +121,35 @@ $ autokara-plot vocals.wav lyrics.ass
 ```
 
 
+# Documentation and useful links
+
+This section is mainly intended for people who would like to contribute and/or are curious about how this stuff works
+
+## Extracting vocals from music
+
+- https://github.com/facebookresearch/demucs
+
+## Syllable segmentation
+
+### Symbolic methods
+
+ - [Syllable segmentation](https://www.sciencedirect.com/science/article/pii/S1877050916319068/pdf?md5=abc426e84a71cd4f5c0e6bef9713643e&pid=1-s2.0-S1877050916319068-main.pdf&_valck=1)
+ - [Syllable segmentation and recognition](https://cdn.intechopen.com/pdfs/15947/InTech-Syllable_based_speech_recognition.pdf)
+ - [Onset detection with librosa](https://librosa.org/doc/latest/onset.html)
+
+### Machine Learning & Deep Learning methods
+
+[Using CNNs on spectrogram images](https://www.ofai.at/~jan.schlueter/pubs/2014_icassp.pdf) (Schlüter, Böck, 2014) :
+ - [MADMOM implementation](https://madmom.readthedocs.io/en/v0.16/modules/features/onsets.html)
+
+[Aligning lyrics to song](https://github.com/jhuang448/LyricsAlignment-MTL) (Jiawen Huang, Emmanouil Benetos, Sebastian Ewert, 2022)
+
+### Other methods
+
+Other stuff goes here
+
+## Syllable recognition
+
+If we ever want to use an AI to identify syllables without a reference lyrics file.
+